| 000 | 03639nam a22005295i 4500 | ||
|---|---|---|---|
| 001 | 978-981-16-7301-6 | ||
| 003 | DE-He213 | ||
| 005 | 20240423125459.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 211204s2021 si | s |||| 0|eng d | ||
| 020 |
_a9789811673016 _9978-981-16-7301-6 |
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| 024 | 7 |
_a10.1007/978-981-16-7301-6 _2doi |
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| 050 | 4 | _aQ334-342 | |
| 050 | 4 | _aTA347.A78 | |
| 072 | 7 |
_aUYQ _2bicssc |
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| 072 | 7 |
_aCOM004000 _2bisacsh |
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_aUYQ _2thema |
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| 082 | 0 | 4 |
_a006.3 _223 |
| 100 | 1 |
_aFarhadinia, Bahram. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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| 245 | 1 | 0 |
_aHesitant Fuzzy Set _h[electronic resource] : _bTheory and Extension / _cby Bahram Farhadinia. |
| 250 | _a1st ed. 2021. | ||
| 264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2021. |
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| 300 |
_aXVII, 151 p. 1 illus. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aComputational Intelligence Methods and Applications, _x2510-1773 |
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| 505 | 0 | _aChapter 1: Hesitant Fuzzy Set -- Chapter 2: Hesitant Fuzzy Linguistic Term Set -- Chapter 3: Neutrosophic Hesitant Fuzzy Set -- Chapter 4: Pythagorean Hesitant Fuzzy Set -- Chapter 5: q-Rung Orthopair Hesitant Fuzzy Set -- Chapter 6: Probabilistic Hesitant Fuzzy Set -- Chapter 7: Type 2 Hesitant Fuzzy Set -- Chapter 8: Hesitant Bipolar Fuzzy Set -- Chapter 9: Cubic Hesitant Fuzzy Set -- Chapter 10: Complex Hesitant Fuzzy Set -- Chapter 11: Picture Hesitant Fuzzy Set -- Chapter 12: Spherical Hesitant Fuzzy Set. | |
| 520 | _aCovering a wide range of notions concerning hesitant fuzzy set and its extensions, this book provides a comprehensive reference to the topic. In the case where different sources of vagueness appear simultaneously, the concept of fuzzy set is not able to properly model the uncertainty, imprecise and vague information. In order to overcome such a limitation, different types of fuzzy extension have been introduced so far. Among them, hesitant fuzzy set was first introduced in 2010, and the existing extensions of hesitant fuzzy set have been encountering an increasing interest and attracting more and more attentions up to now. It is not an exaggeration to say that the recent decade has seen the blossoming of a larger set of techniques and theoretical outcomes for hesitant fuzzy set together with its extensions as well as applications. As the research has moved beyond its infancy, and now it is entering a maturing phase with increased numbers and types of extensions, this book aims to give a comprehensive review of such researches. Presenting the review of many and important types of hesitant fuzzy extensions, and including references to a large number of related publications, this book will serve as a useful reference book for researchers in this field. | ||
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aComputational intelligence. | |
| 650 | 1 | 4 | _aArtificial Intelligence. |
| 650 | 2 | 4 | _aComputational Intelligence. |
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9789811673009 |
| 776 | 0 | 8 |
_iPrinted edition: _z9789811673023 |
| 776 | 0 | 8 |
_iPrinted edition: _z9789811673030 |
| 830 | 0 |
_aComputational Intelligence Methods and Applications, _x2510-1773 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-16-7301-6 |
| 912 | _aZDB-2-SCS | ||
| 912 | _aZDB-2-SXCS | ||
| 942 | _cSPRINGER | ||
| 999 |
_c178395 _d178395 |
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